University Of California-Irvine

NSF Awards · FY 2025 · 2025-07

This project addresses theoretical challenges in high-dimensional probability, with a particular focus on those arising in data science. It aims to develop rigorous mathematical foundations for understanding the authenticity and privacy of synthetic data, tackling questions such as “What is artificial, mathematically?” and “How can we distinguish artificial data from real?” As a related aim, the project will broaden the reach of random matrix theory in data science by developing new geometric approaches to random matrices and random tensors. By establishing a probabilistic framework for detecting synthetic data, the project will develop an adversarial classification model and characterize the regimes where artificial data can be reliably identified. This analysis will draw on connections to high-dimensional Gaussian geometry and convexity. To develop a mathematical framework for private synthetic data, the project will explore metric-based characterizations of the privacy-accuracy tradeoff, grounded in the methodology of high-dimensional probability. Furthermore, this project will advance non-spectral random matrix theory by developing and applying high-dimensional probability methods to study approximation numbers, general operator norms, and norms of the inverse of random matrices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-07

With approximately 296 million people (5.8% of the global population aged 15–64) having used drugs at least once, the world is facing an unprecedented opioid epidemic. Chronic opioid exposure can lead to long-term brain function changes and opioid use disorder (OUD). Concurrently, despite advancements in treatment that have transformed HIV into a manageable chronic disease, evidence shows that opioid use in HIV-infected individuals can further weaken immune function and exacerbate HIV-related central nervous system (CNS) impairments. To unravel the intricate interplay between these conditions, several SCORCH data generation and analysis centers have been funded to generate large-scale molecular profiling data at single-nuclei resolution, allowing the revelation of cell-type-specific molecular alterations due to chronic opioid exposure and/or HIV infection. However, the driving forces behind these molecular changes and their underlying regulatory mechanisms remain elusive, hindering our understanding of these factors and limiting the development of effective therapeutic strategies. To address this gap, we propose the DMFV-SCORCH project, an interdisciplinary initiative aimed at uncovering multi-scale dysregulations resulting from HIV and OUD through population-scale single-nuclei sequencing data, and validating our findings with advanced genomic assays. Specifically, we aim to identify intra- and inter-cellular dysregulations that lead to transcriptomic alterations and brain dysfunctions in OUD and HIV. We will address three key questions: 1) Which cell types are significantly affected, and what epigenetic changes lead to differentially expressed genes (DEGs) in these cell types? 2) Within a cell, what alterations in the gene regulatory network (GRN) and 3D chromatin conformation contribute to the DEGs? 3) How do regulatory changes in the CNS microenvironment, via cell-cell communications (CCC), impact DEGs? To achieve this goal, we will: 1) develop advanced Artificial Intelligence (AI) methods for data mining on SCORCH and atlas-level public CNS single-nuclei sequencing data, highlighting multi-scale dysregulations due to HIV/OUD; and 2) conduct functional validations through advanced genomic assays, such as epigenetic and transcriptomic manipulations via CRISPR followed by snRNA-seq (e.g., CROP-seq) and high-throughput screenings using massively parallel reporter assays (MPRA). Collectively, our examination of the interrelationships among genetic, epigenetic, transcriptional, network, and inter-cellular dysregulations will offer a robust translational approach to unravel the independent and synergistic mechanisms of OUD and HIV.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY Smoking has been demonstrated to induce oxidative stress, which is compounded with significantly reduced antioxidant availability, increased production of inflammatory cytokines as well as neutrophilic infiltration that are implicated in pathogenic processes in the lungs. Additionally, studies involving mice exposed to cigarette smoke reveal impaired pulmonary anti-bacterial and anti-viral defenses in response to infections. Other research has found that smokers also exhibit increased susceptibility to infections including influenza and SARS-CoV2. Investigations concerning the harmful effects that tobacco use exerts to lower bodily defenses are undeniably urgent, particularly those that address strategies for amelioration of smoking-induced health risks. Nicotine is the main component among the thousands of chemicals in all tobacco products including e-cigarettes. Nicotine binds to a family of nicotinic acetylcholine receptors (nAChRs) like acetylcholine (ACh). nAChRs are highly expressed in the lung fibroblasts and epithelial cells. Nicotine functions as an immunomodulator and has been reported to impair the immune response of smokers to infections. Vitamin C (vitC; ascorbic acid: AA) is an essential water- soluble vitamin with known respiratory health enhancing properties. Humans cannot synthesize vitC endogenously and thus obtain it from dietary sources via intestinal absorption. Dietary vitC is absorbed from the intestine via carrier-mediated sodium-dependent vitC transporters (SVCT1 and SVCT2, the products of the SLC23A1 and SLC23A2 genes, respectively). Low plasma levels of vitC have been found in patients with viral infections and other critical illnesses. Many previous studies have highlighted the role of vitC in protection against lung infections. Administration of vitC to patients with pneumonia, for example, can reduce the severity and duration of the disease. Pneumonia and influenza infections and related pathologies are also more severe in Gulo KO mice (a mouse model that cannot synthesize vitC endogenously, similar to humans). Both smokers and passive smokers have lower plasma and leukocyte vitC levels than non-smokers. Mean serum concentrations of vitC in adults who smoke have been found to be one-third lower than those of non-smokers. Our preliminary studies showed that nicotine reduces the functional expression of vitC transporters in the intestine and lung epithelial cells. We therefore hypothesize that nicotine induced vitC deficiency/insufficiency is a major factor in increasing the risk of respiratory viral infections in smokers. To test this hypothesis we propose two specific aims: Aim 1: To determine the mechanisms underlying nicotine-mediated impaired uptake of vitC by intestinal and lung epithelial cells using in vitro and in vivo models. Aim 2: To determine whether vitC supplementation is able to overcome the increased susceptibility to viral infections induced by nicotine. The expected outcomes of this project will advance our knowledge regarding the changes in uptake of vitC in the intestine and in the lungs, which is essential to develop novel therapeutics to improve vitC deficiency and insufficiency while also addressing ensuing lung viral infections and injury found in smoking population.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY Chronic infections like HIV, HBC and HCV and cancers that evade the immune system continue to impact the lives of millions of patients worldwide causing high morbidity and mortality. It is now evident that during persistent antigen, CD8+ T cells become phenotypically and functionally exhausted. Continuous TCR stimulation, high expression of multiple inhibitory receptors, and multiple immunosuppressive mechanisms limit effector T cell functions. T cell exhaustion is observed in chronic infections in murine, monkey, and human hosts. Immune checkpoint blockade (ICB) can reinvigorate exhausted T cells and improve pathogen and tumor control in mice and patients. These drugs are now standard treatments for cancer, but at present are effective only in very few patients, highlighting the need to identify additional immunotherapies aimed to enhance the quality and quantity of the responding T cells to help improve patient outcomes. Our previous findings have identified Serine/threonine-protein phosphatase 6 (PP6) regulatory subunit 3 (SAPS3) as a negative regulator of AMPK. Preliminary data reveal that SAPS3 is highly expressed and upregulated on exhausted CD8+ T cells during infection. Mice with SAPS3 deletion exhibit increased frequencies and numbers of virus-specific CD8+ and CD4+ T cells, with enhanced functionality and increased mortality compared to wild-type (WT) mice following Cl13 infection. In addition, we found that inhibitor receptors were lower on virus-specific CD4+ and CD8+ T cells in Saps3-/- mice. Mechanistically, we observed increased AMPK activity and metabolism in Saps3-/- CD8+ T cells compared to WT only after Cl13 infection. Our data also showed that after acute LCMV Arm infection, Saps3-/- mice develop higher frequencies and numbers of functional CD8+ T cells. Based on our preliminary data, we plan to test the central hypothesis that SAPS3 is a key negative regulator of CD8+ T cells through regulation of AMPK and metabolism during chronic viral infection. The proposed research will provide a mechanistic analysis of how T cells are regulated during viral infection. We will test our hypothesis by pursuing the following three specific aims 1) To determine the role of SAPS3 in virus-specific T cells during acute and chronic viral infection 2) To elucidate the molecular mechanisms by which SAPS3 regulates T cell activation 3) To evaluate the therapeutic potential of combining Saps3 deletion and immune checkpoint blockade (ICB) in therapy sensitive vs resistant tumors. This contribution will be significant because understanding how metabolic regulators fundamentally function in T cells has the potential to lead to the development of therapeutic interventions targeting these pathways to modulate T cells and help prevent and/or treat patients with chronic infection, cancer, or autoimmunity.

NSF Awards · FY 2025 · 2025-07

In this project, the PI will develop new approaches to elucidate and apply the notion of symmetry, a unifying principle within modern mathematics that has important applications in theoretical physics, and cryptographic systems. The research will be organized around two research streams: one is to understand the structure of "higher" continuous symmetries which first emerged in investigations in theoretical physics in the early 1990s, and the second is to explore discrete symmetries arising in algebraic equations, which play an essential role throughout science and engineering. By studying the symmetries of these equations, the PI will find deeper ways to solve them, and to measure the ease or difficulty of finding their solutions. Alongside this work, the PI will contribute to the mathematical training of STEM learners from middle school on up. The two streams used by the PI can be encapsulated as "higher Lie theory" and "resolvent problems". Both build upon fundamental inquiries at the interface of group theory, geometry and topology, and homotopical algebra. For the first major stream, the PI will establish analogues of Lie’s Second and Third Theorems for finite type L-infinity-algebras and finite dimensional Lie infinity-groups. For the second major stream, the PI will continue his ongoing investigation of resolvent problems and Hilbert’s 13th problem in three interrelated ways: a) initiating the study of resolvent degree of finitely generated groups, with a focus on braid groups and arithmetic lattices; b) developing new methods for generating solvable points on varieties, and use this to give p-adic analogues of Klein’s modular solutions of polynomials of low degree (with a focus on degree 8 and below); and most speculatively, c) seeking to find invariants capable of detecting nontrivial lower bounds on resolvent degree. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

The goal of the UCI Medical Scientist Training Program (MSTP) is to train students as biomedical research scientists who will make advances to improve the diagnosis, understanding and treatment of human diseases. Training is offered in a diverse number of medically related fields. This is accomplished by means of a flexible, independently designed curriculum. MSTP students can complete their PhD studies in any graduate program at UCI. These include departments and graduate programs in all 14 schools and the Program in Population & Public Health, which is in the process of becoming a school. In addition, students may carry out their research in one of the collaborative facilities on campus that combine both basic and clinical research, such as the Beckman Laser Institute and Medical Clinic, the NCI Chao Family Comprehensive Cancer Center, the Institute for Clinical and Translational Science and the Sue & Bill Gross Stem Cell Research Center. Students have pursued their graduate research in the Schools of Medicine, Biological Sciences, Engineering, Social Ecology, Physical Sciences, and Information & Computer Sciences, as well as the Program in Public Health. Opportunities for research also include numerous collaborative facilities on campus that combine both basic and clinical research, such as the Beckman Laser Institute and Medical Clinic, the Research Imaging Center, the NCI Chao Family Comprehensive Cancer Center, the Institute for Clinical and Translational Science and the Sue & Bill Gross Stem Cell Research Center. Established in 1987, the MSTP has enrolled 216 students and has graduated 119. There are currently 63 students in 20 departments across 9 schools or programs. There were 74 alumni who graduated since 2008, with 27 still in residency or fellowship training, and 1 deceased, leaving 46 who have completed their training and obtained positions. Of this group, 25 (54.4%) are in faculty positions, 3 (6.5%) are in industry (which includes a lab director), 6 (13.0%) are at academic medical centers, and 12 (26.1%) are involved exclusively in clinical care. The program enrolls 7 new students each year using a holistic admissions process that includes academic performance, research experience and potential, clinical experience, and personal characteristics and experiences, including factors contributing to educational diversity. Students have been quite productive, with an average of 6.7 papers per student and 2.9 first author papers per student for graduates during the past 10 years. They study with faculty who have strong training records and research grant support that averages ~$500,000 annually. All students are fully supported.

NIH Research Projects · FY 2025 · 2025-07

Project Summary/Abstract Peromyscus leucopus, the white-footed deermouse, is a natural host and major reservoir for the agents of Lyme disease, anaplasmosis, and babesiosis among other zoonoses in North America. The related species P. maniculatus is a reservoir for hantavirus as well as Lyme disease. While mouse-like in appearance, these deermice are more closely related to hamsters and voles than to Mus or Rattus. P. leucopus also has longevity 2-3 times that of the house mouse and has a more restrained inflammatory response to TLR agonists and infection. While translational interest in P. leucopus increases, including as a target for field vaccines and for genetic modification and then environmental release, there are very limited tools besides genome-wide and targeted RNA-seq for in-depth study of the immunology and host responses of these animals. Examples are reagents and assays for flow cytometry and IgG subclasses. Antibodies for phenotyping white cells that are developed for study of mice or humans seldom have sufficient cross-reactivity with deermouse orthologous proteins to succeed. This application for a 2-year developmental project recognizes this need for the field to advance and proposes to take the first steps to remedy the deficiency. Using our access to a closed colony of P. leucopus that is representative of wild populations in terms of genetic diversity, we will carry out work on the following specific aims: Aim 1. Antibodies for phenotyping leukocytes of Peromyscus. First will be a pan-leukocyte monoclonal antibody suitable for flow cytometry and sorting. The isolated leukocytes from different outbred deermice will be subjected to multiplexed scRNA-seq, the results of which provide either confirmation of provisional choices (i.e. CD14 and CD19) or guidance on alternatives for marker antibodies of narrower specificity. Aim 2. IgG subclasses of Peromyscus. Using the deduced amino acid sequences for constant regions of heavy chains, we will characterize and measure subclasses by LC-MS/MS. Discriminating peptides will be used for eliciting sub-class specific antibodies. The affinities of different subclasses for Fc receptor ligands, like Protein A will be assessed. Aim 3. Application of tools to models of systemic inflammation and of infection. The utility and informativeness of the outcomes of Aims 1 and 2 will be assessed in our established P. leucopus models of infection with B. burgdorferi or systemic inflammation from TLR agonists.

NSF Awards · FY 2025 · 2025-07

This I-Corps project is based on the development of a software platform to provide a wide range of computer vision tasks with minimal computational effort for mobile applications, including autonomous vehicles, robotics, and traffic monitoring. Currently, traditional models using artificial intelligence (AI) solutions are static, monolithic, and optimized for worst-case scenarios, leading to significant computational demands that mobile devices often cannot meet. This technology provides operators with real-time, actionable insights, even in low-bandwidth environments. The solution is based on a new generation of AI algorithms, empowering systems with new analysis capabilities. In addition, it uses a modular approach that is designed to integrate seamlessly with existing systems, which may ensure greater scalability and adaptability for rapidly evolving missions. The ability of the platform to deploy AI algorithms in a flexible, resilient, and distributed fashion may make it possible to gather information from multiple sources from the environment, understand what the information means, and use the information to predict what may happen next, referred to as dynamic situational awareness. This technology may improve the decision making and safety of first responders and workers across fields and commercial areas and improve U.S. defense capabilities. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of a software platform to provide a wide range of computer vision tasks by leveraging adaptive sensor fusion and edge processing. Computer vision is the cornerstone of a broad range of current and future mobile applications, such as vehicular autonomy, robotics, and traffic monitoring. In this domain, deep neural networks (DNN) achieve the best performance, where many generations of models have been designed to accomplish various tasks. Currently, these algorithms are designed for execution on a single machine and are static and monolithic. One downside of this approach is that the algorithms are tuned to process the “worst” case input, and have computational demands often failing to meet application requirements when considering the limitations of mobile devices. Moreover, offloading the execution to compute-capable devices (edge computing) requires the transfer of information-rich signals (e.g., camera, light detection and ranging (LiDAR) and radar imaging) over capacity constrained and volatile wireless channels. The goal is to provide operators with real-time, actionable insights, even in low-bandwidth or contested environments. The ability of the platform to deploy AI algorithms in a flexible, resilient and distributed fashion may make it possible to provide dynamic situational awareness in a broad range of applications. This may bring a new generation of AI algorithms to the market, empowering vehicles with new analysis capabilities that may improve decision making and safety. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY Nicotine products are a major public health problem worldwide, causing millions of deaths per year. The US government spends billions of dollars annually in healthcare costs due to nicotine-related illnesses. Further, electronic cigarette usage has skyrocketed, conferring additional addiction liability among the population. Most people using nicotine products report wanting to quit, but the vast majority are not successful in the long term. Cessation aids available, including nicotine replacement therapy, varenicline and bupropion, have limited long term efficacy. Recent research in our lab has focused on alternative targets for cessation aids, such as targeting the G-protein coupled receptor 3 (GPR3), an orphan receptor with promising results in mitigating nicotine intake. GPR3 is an orphan, Gas coupled receptor that exhibits constitutive activity. GPR3 is expressed in brain regions that mitigate nicotine intake and preliminary data shows that a GPR3 agonist decreases nicotine self- administration in male and female mice. It is unknown, however, if drug exposure regulates GPR3 expression in brain regions related to nicotine intake and withdrawal. It is also unknown how the GPR3 agonist alters the actions of nicotine on a cellular level. Further, we do not know the effects of GPR3 activity on nicotine withdrawal. To address these gaps in the field, this proposal aims to investigate environmental factors that influence GPR3 gene expression, effects of the GPR3 agonist on cell excitability and the effects of the GPR3 agonist on nicotine withdrawal. Because of the high GPR3 expression and known involvement in nicotine intake and withdrawal, the medial habenula will be the focus of the expression and electrophysiological experiments in this proposal. Aim 1 will test the effects of nicotine exposure on GPR3 expression in the medial habenula. For these studies, the effect of repeated nicotine exposure will be tested on their effects on GPR3 mRNA expression in the medial habenula. Aim 2 will test the effects of the GPR3 agonist on cell excitability in the medial habenula. For these studies, patch clamp electrophysiology will be used to determine the effects of the GPR3 agonist on cell firing frequency. The GPR3 agonist will be given in combination with nicotine to reveal the effects of GPR3 activity on nicotine-induced cell excitability. Lastly, aim 3 will test the effects of the GPR3 agonist on nicotine withdrawal symptoms in mice. Mice will be exposed to a nicotine vapor protocol that has been validated to increase nicotine withdrawal symptoms. For withdrawal testing, mice will be treated with the GPR3 agonist directly prior to testing in order to determine its effects on mitigating nicotine withdrawal symptoms. All studies in this proposal will be powered to detect sex differences, if any exist. Overall, these studies will provide insight into biological and environmental factors which may influence GPR3 expression, reveal the effects of a GPR3 agonist at a cellular level, and determine effects of GPR3 agonism on nicotine withdrawal symptoms.

NSF Awards · FY 2025 · 2025-07

Early life experience is more varied than we often realize. For children coming of age in families where the language spoken at home differs from the language of the larger community, exposure to two languages typically produces bilingualism. Using a home language different than the language spoken outside by the larger society, called heritage bilingualism, is the most common form of bilingualism in this country although it has not been an area of much investigation. A feature of heritage bilingualism is that children in this context are often called upon to translate for their caregivers. The stronger language skills that the children in these contexts come to have, particularly once they enter school, enable them to become brokers or translators for their caregivers, who may only speak the home language or may have only partial knowledge of the language of wider communication. Language brokering may involve translating conversations, documents, and providing language support in medical settings. The focus of the research in the current project is on the consequences of this translation or brokering experience once these children become young adults. The researchers hypothesize that the highly dynamic use of both languages required to broker will be associated not only with more integrated language representations but also with a greater ability to regulate the effective use of the two languages under a range of communicative contexts. The team takes a novel approach by analyzing young adult bilinguals’ brain and behavior to examine the impact of language brokering on language processing and cognition. They ask whether this early life experience of intensive translation creates enduring consequences for young adult bilinguals. Outcomes of this study bring awareness to the cognitive affects of language brokering, thus contributing to demystifying views of bilingualism. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMMARY/ABSTRACT Transcriptional enhancers are non-coding DNA elements that control the expression of their target genes with spatiotemporal specificity. Transcription factors confer the specificity of enhancer function by recruiting core transcriptional machinery to the enhancer’s target promoter during gene activation. Altered enhancer function may yield a variety of pathologies, including congenital anomalies. However, even under adverse environmental and genetic conditions, most births occur without congenital anomalies, attesting to the resilience of developmental programs. This “developmental robustness” may rely on the fact that most genes expressed during development are controlled by multiple redundant enhancers with overlapping spatiotemporal activities, so-called shadow enhancers. However, despite the ubiquity of these shadow enhancers, we do not completely understand how they confer developmental robustness. Using a mouse model of limb morphogenesis and genetic engineering at the mouse Gli3 genomic locus, I generated preliminary data suggesting that shadow enhancers are activated by distinct transcription factor inputs, despite their apparent redundancy. This “separation of transcription factor inputs” may be significant to shadow enhancers’ roles in supporting developmental robustness. The primary objective of this proposal is to identify the distinct transcription factors driving each shadow enhancer (Aim1) and characterize how two distinct shadow enhancers organize in the three-dimensional space of the nucleus during gene activation (Aim2). To achieve Aim 1, I will perform a genomic footprinting technique to determine which transcription factor binding sites are occupied within each shadow enhancer during gene activation. This approach will be complemented with an in vivo enhancer-reporter assay to functionally test for the requirement of each binding site. To accomplish Aim 2, I will perform three-color DNA fluorescence in situ hybridization (DNA-FISH), which will allow me to measure the co-localization of two shadow enhancers and the Gli3 promoter under different genetic conditions. The proposed research will unveil the molecular and spatial mechanisms of gene regulatory redundancy during mammalian development. Providing his expertise in gene regulation, mouse transgenics, and developmental biology, Dr. Evgeny Kvon will serve as my sponsor during the fellowship period. With consultation from Dr. Kvon, I have developed a robust training plan to facilitate my transition to becoming an independent investigator and biology educator. Under this proposal, I will learn new skills in genomics, DNA-FISH, transgenics, and bioinformatic analysis. My professional development will encompass training in scientific communication, teaching, and mentorship.

NIH Research Projects · FY 2025 · 2025-07

The goal of the proposed T32 Postdoctoral Program is to provide a robust mentored career development and training environment that pursues the following specific aims. Specific Aim 1: Champion mentored career development and training by nurturing an integrated T32 Postdoctoral Program that consists of outstanding leadership and oversight at all levels. An essential requirement for the program is outstanding leadership and strong oversight. Our Education Leadership Team (ELT) consists of Program Directors, Associate Directors, and a Program Administrator. The ELT works closely with the ICTS UM1 Workforce Development Module Team (WDT), the T32 Internal Advisory Committee (IAC), and a nationally recognized ICTS Survey Evaluation Tracking (SET) Team. The oversight of the program is highlighted by our Trainee- Mentor Alignment and Individual Development Plan meetings, a strong SET process, and a Quality by Design paradigm. Our ICTS partners [Children’s Hospital of Orange County (CHOC) and Long Beach Veterans Association Hospital (LBVA)] will participate in our IAC and quarterly meetings with the ELT. Specific Aim 2: Maximize access to the T32 Postdoctoral Program. We will: 1) support the training of two ICTS T32 trainees per year; 2) continue our Affiliated Scholars Advancement Program (ASAP), which significantly expands training opportunities for unfunded trainees interested in pursuing Clinical Translational Science and Research (CTS&R); and 3) continue to recruit highly-qualified trainees from all backgrounds. Specific Aim 3: Provide a flexible and innovative curriculum that emphasizes both core competencies and advanced concepts in CTS&R. Focused Flexible Accelerated Studies (FFASt) is an immersive set of courses and experiential opportunities developed to expose our trainees to core and advanced competencies in CTS&R. FFASt courses also play a central role in our extensive Responsible Conduct of Research and Reproducibility curriculum. Our FFASt curriculum has always included key elements necessary for nurturing the development of our trainees becoming more proficient as: 1) domain experts, 2) boundary crossers, 3) team players, 4) process innovators, 5) skilled communicators, 6) systems thinkers, and 7) rigorous researchers. Our monthly Journal Clubs include modules which provide additional focus on these key skills. Specific Aim 4: Integrate local, regional, and national insights to transform CTS&R training. The breadth of our program’s integration at the local and regional levels is highlighted by key elements such as: 1) T-ECO, which is a survey of the training landscape at UC Irvine, CHOC, and LBVA, and is used to inform our T32 program and key leaders throughout our campus, 2) a campuswide KT PI Training Council we created and lead, 3) our leadership in developing a campuswide Training Day, and 4) the Western CTSA Education consortium, which consists of 11 CTSAs from California, New Mexico, Oregon, and Washington. In accordance with our driving theme, we are committed to transforming the CTS&R training environment at the local, regional, and national levels.

NSF Awards · FY 2025 · 2025-07

Animals and plants host communities of bacteria and other microorganisms—known as microbiomes—that are essential for health. A central goal of microbiome science is to discover what causes the microbiome to change, and the broader consequences of such change. A consistent pattern emerging from this research is that the microbiome is seasonal: an animal in spring, for example, will have a very different microbial makeup from one in fall. But what causes the microbiome to change? And do seasonal microbiome changes influence the timing of critical biological events, such as hibernation? Answers are urgently needed, because increasingly erratic and extreme weather is knocking the life cycles of animals and plants out of sync, and in turn, jeopardizing wildlife populations and the many services they provide to society. How the microbiome is involved, and how it may be harnessed to maximize the stability of natural and agricultural ecosystems, are currently unknown. This project will focus on these open questions through experiments and field studies involving bumble bees. General principles resulting from this research will ultimately improve prediction and management of microbiome change in wildlife. Further, findings will inform specific strategies to protect bumble bees, a threatened group of pollinators that is vital for agriculture. This project will also support educational initiatives designed to help grow the science and technology workforce. The researchers will train teachers in scientific practices through a workshop and co-create an experiential learning program for high school students in Anaheim, CA. Finally, a course will be developed at the University of California, Irvine, in which undergraduate students actively participate in microbiome experiments. This project will develop bumble bees as a model organism with which to determine general drivers and life-history consequences of microbiome seasonality. Researchers will use microsensors and microscopy to discover how seasonally changing environmental factors within the host influence, and are influenced by, the microbiome. Roles of host development and microbial spillover in microbiome seasonality will be tested by tracking transmission of genetically labeled bacteria in bumble bees and co-reared solitary bees over time. Researchers will also recreate microbiome seasonality under controlled conditions to determine whether it actively regulates host reproductive timing and fitness. The research will be integrated with educational initiatives in multiple ways, and survey data will assess the degree to which these programs increase student recruitment into science and technology fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

Many important and classical results in mathematics show that certain tasks are impossible. Examples are “you can’t square the circle” or that “the square root of two cannot be expressed as a fraction of natural numbers.” Important recent applications of these types of results are in cryptocurrency and cryptography . There are certain problems in mathematics that were posed about a century ago that are still not solved. The research in this grant explains why: the current techniques for solution can be proved to be not strong enough to solve them. The project involves graduate students. Between problems that can be solved with inherently finite (i.e., recursive) information and problems that require the uncountable Axiom of Choice to solve (such as the existence of a non-Lebesgue measurable set), there are problems that cannot be solved using inherently countable information. This project shows that classical problems of von Neumann from the 1930s about ergodic theory and of Poincaré about qualitative dynamics at the turn of the 20th century cannot be solved using inherently countable information. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

Project Summary The emergence and spread of SARS-CoV-2 variants of concern is threatening global health and our ability to prevent COVID-19 disease, raising concerns about a potential new wave of the pandemic. HIV may complicate the trajectory of the COVID-19 pandemic and efforts to eradicate the virus. While most people with a competent immune system successfully clear SARS-CoV-2 infection within days, people living with HIV with weakened immunity can carry persistent infection for months. Individuals with immunodeficiency may also have a higher risk of SARS-CoV-2 reinfection that can further extend the duration of infectiousness with high viral load. As a result, chronically infected individuals are potentially contagious for an extended period of time and may sustain transmission in the community. Similar to other viruses, SARS-CoV-2 accumulates mutations over time as it replicates within the host. Therefore, chronic SARS-CoV-2 infection in the context of a weakened immune system may provide the time and the environment needed for the virus to replicate and evolve genetic mutations associated with survival advantages, including increased transmissibility and resistance to COVID-19 vaccines or treatment. The proposed research aims to understand the overall impact of HIV infection on the SARS-CoV-2 viral evolution and transmission dynamics in a setting with high HIV prevalence. We will address current knowledge gaps by integrating SARS-CoV-2 genomic data, patient-level clinical data, and epidemiological data to achieve the following aims: 1) we will determine the effect of HIV infection on the transmission dynamics of COVID-19 and emergence of SARS-CoV-2 variants; and 2) we will determine the effect of HIV-associated immunosuppression on the acquisition of SARS-CoV-2 mutations. For the first Aim, advanced phylodynamic methods will be applied to determine how HIV affects the transmission and viral evolution of SARS-CoV-2 on a population scale, as well as to describe risk factors that drive individual and population-level COVID-19 transmission. For the second Aim, we will recruit and follow a cohort of COVID-19 patients with and without HIV infection to determine the effect of HIV-associated immunosuppression on the rate of emerging SARS-CoV-2 mutations. The proposed research will also utilize active case finding to minimize sampling bias. Findings from this project will inform the development of optimal public health interventions to control the pandemic by disrupting transmission chains and prevent the emergence and spread of alarming variants.

NIH Research Projects · FY 2024 · 2025-07

1. Project Summary/Abstract: Research Overview – Research is focused on organic synthesis, particularly on developing strategies and modes of reactivity that facilitate construction of complex molecules of medicinal and/or biological value. We have developed over thirty-five stereoselective reactions based on areas of reactivity that include metallacycle-mediated cross-coupling, [3+2] cycloaddition, vinylcyclopropane rearrangement, radical cascade chemistry, and tandem oxidative dearomatization/Wagner–Meerwein rearrangement. While some of these have been developed with the goal of realizing a wide range of unique “convergent” C–C bond forming processes, others have emerged in natural product synthesis projects. These combined activities, that aim to advance the fundamental backbone of organic chemistry through innovation within the field of stereoselective synthesis, are routinely embraced as enabling technology to fuel exploration in medicinally relevant science; examples included: (1) a non-opioid analgesic (conolidine), (2) paralog selective Hsp90 inhibitors (benzoquinone ansamycins), (3) selective anti multiple myeloma agents (lehualide B), (4) the first non-peptidic selective ligand to the DBD of p53 (natural product-inspired oligomerization), (5) the most potent and selective agonist of the estrogen receptor beta (ERb), (6) ent-steroids as potent and selective modulators of the glucocorticoid receptor, (7) substituted estranes and androstanes as antagonists of the androgen receptor (AR), (8) a designed enantiodefined hydrindane as the most potent inhibitor of the transcription factor ToxT, (9) steroidal ligands that interrupt the binding of NEMO to Ikkb, and (10) acyclic mimetics of oleic acid as potent and selective functional ligands to GPR40, GPR120 and TLX. Overall Vision for the Program – This seamless integration of reaction development, natural product synthesis, and efforts to employ our technology as an enabling tool for the discovery of molecules with unique biological properties defines the basic fabric of science that is the focus in my laboratory. Goals for the Next Five Years – Efforts will focus on natural product- and function-oriented synthesis, reaction development, and the design and synthesis of synthetic steroid- and fatty acid-like agents as potent and selective modulators of NRs and GPCRs. These activities will include target-oriented synthesis campaigns around limonoids, cardenolides, b-agarofurans, and the stelletin class of natural products. All of these planned efforts have, at their core, the ambition to establish and demonstrate novel synthesis designs and reaction methods to address a wide range of complex natural products and molecules of great potential biomedical relevance. Because our efforts include the exploration of new reactions and synthesis strategies as enabling tools/methods for the invention of molecules designed to modulate particular receptors (as summarized above), we will also continue to pursue opportunities to evaluate the molecular products of this synthetic chemistry-focused program (e.g., CROs like Indigo Biosciences and Eurofins Discovery services).

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY/ABSTRACT Tick-borne Rickettsia species cause serious human disease in the United States and worldwide, including spotted fever and typhus, with no approved vaccines and an increasing incidence of infection. R. rickettsii is the causative agent of Rocky Mountain spotted fever, and the closely related R. parkeri causes spotted fever in North and South America. However, due to their obligate intracellular nature and technical challenges, the interactions between Rickettsia and innate and adaptive immunity remain largely unclear. Elucidating how Rickettsia evade innate immunity and stimulate an adaptive response is critical for developing effective vaccines and therapeutics to better understand, prevent, and treat human disease. In preliminary work, we performed a forward genetic screen to identify for the first time the rickettsial factors required for survival in primary mouse macrophages. Two of the most attenuated mutants contained insertions in the genes rmlD and wecA, which are required for biosynthesis of O-antigen, the external component of lipopolysaccharide. We found that O-antigen is required to avoid targeting by ubiquitin and inflammasomes. However, the underlying mechanisms by which O-antigen enables R. parkeri to evade these innate immune defense systems remain unclear. Moreover, O-antigen and outer membrane proteins (OMPs) are both implicated in the adaptive response, yet it is unclear how O-antigen and OMPs protect against T cells and antibodies. Thus, key outstanding questions include: which Rickettsia factors enable survival in immune cells? What are the molecular mechanisms by which O-antigen enables R. parkeri to avoid ubiquitin and inflammasomes? And, what are the relative contributions of O-antigen and OMPs to the adaptive response? We will answer these questions by comprehensively identifying the R. parkeri virulence factors required for survival in macrophages by performing an innovative forward genetic screen. We will reveal the underlying mechanisms by which Rickettsia virulence factors including O-antigen protects from ubiquitin by identifying the E3 ligase(s) that target R. parkeri. We will use electron microscopy to determine if O-antigen composes the capsule, which may shield against E3 ligases, and will measure the degree to which O-antigen protects from autophagy and inflammasomes. In vivo, we will determine how O-antigen protects against innate immunity during acute infection and the relative contributions of O-antigen and OMPs to protection against antibodies and T cells. We will innovate by using unbiased genome-wide protein microarrays to identify novel rickettsial antigens targeted by antibodies. Such antigens may serve as novel vaccine candidates. Together, these studies will leverage our expertise in bacterial and host genetics, cell biology, and in vivo infection models to discover mechanisms by which an obligate intracellular pathogen evades innate immunity, with clinical importance of revealing mechanisms of immunity and identifying novel antigens for vaccines.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT Oligonucleotide therapeutics (ONTs) are poised to ignite a paradigm shift in what constitutes a “treatable” human disease. The FDA approval of life-changing ONTs like Spinraza (Ionis’ ASO therapy for spinal muscular atrophy), Onpattro (Alnylam’s siRNA therapy for hATTR amyloidosis), and the mRNA-based COVID-19 vaccines from Pfizer and Moderna that saved millions of lives demonstrate the profound potential impact ONTs can have on “undruggable” diseases. CRISPR-based editing strategies are now entering the clinic, with lipid nanoparticle-mediated delivery of mRNA encoding Cas9 variants offering an alternative to problematic viral vectors. Suppressor tRNAs that read through premature stop codons to restore proteins that were “lost in translation” are moving towards the clinic. Each of these ONTs faces a shared barrier to broad clinical translation: biological membranes. The large size (5-35 kD) and charged backbone of ONTs severely limits their ability to cross the plasma membrane. Even if the plasma membrane is crossed by promoting the endocytosis of the ONT, the endosomal membrane remains a highly effective barrier that prevents ONTs from reaching their targets in the cytosol and nucleus. Estimates are that only 1-3% of the ONT delivered to a patient reaches its target - the delivery stats are dismal for naked, ligand-conjugated, and LNP-encased ONTs. ONTs tend to accumulate in the liver, and most FDA-approved ONTs that are delivered systemically have liver targets. ONT conjugation to GalNAc, the ligand for the asialoglycoprotein receptor expressed on hepatocytes, improves delivery 30-fold. Other approved agents rely on local delivery to increase ONT exposure to a level sufficient to provide clinical value. However, not all tissues are suited for local delivery, many cell types with these tissues remain inaccessible to ONTs, and local delivery risks infection or damage to the target organ. There is thus a critical unmet need for strategies that improve the delivery of systemically administered ONTs to extrahepatic tissues. Until this need is met, a revolution in medical practice ushered in by nucleotide-based therapies will remain a dream unrealized. This proposal seeks a small molecule solution to the delivery problem. This strategy would be effective for multiple ONT platforms and disease agnostic. By drilling down on rigorous target validation from the outset, we hope to initiate a successful drug development program that takes the most direct path to the clinic. Our lead compounds diverge from status quo potentiators in that they dramatically increase ONT activity without causing endosomal damage, an effective, but prohibitively toxic, mode of action. The expected results would provide a solid foundation for funding a successful lead optimization program supported by target engagement assays and highlight the diseases most likely to rapidly realize the benefits of this approach.

NSF Awards · FY 2025 · 2025-06

This I-Corps project is based on the development of a digital software platform for healthcare research. Researchers currently face obstacles that limit innovation including high costs, fragmented tools, and technological complexity when conducting real-world studies. This technology addresses the inefficiencies and technical barriers that hinder traditional clinical studies by providing an integrated, intuitive system that automates data collection, participant engagement, and real-time analysis. The solution is designed to enable research teams to deploy advanced digital health studies without writing a set of instructions (computer code) or building custom infrastructure. In addition, the solution includes wearable sensor technology, behavior-triggered surveys, and artificial intelligence (AI) analytics to support dynamic, adaptive clinical research. The technology may enhance study accuracy, efficiency, and participant adherence, which may lead to faster and more effective healthcare solutions. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a digital research software platform that integrates multimodal data collection, intelligent intervention delivery, and real-time analytics. The technology is a no-code, closed-loop system that utilizes context-aware mobile health technologies, wearable device streams, and advanced machine learning models to facilitate predictive analytics and adaptive study management. Compared with current technology that is often siloed or requires manual integration, this system centralizes control through a unified interface while allowing for complex study design without coding expertise. In addition, the solution includes automated adherence tracking, environmental and behavioral context sensing, and scalable data pipelines that support real-world evidence generation. The technology’s artificial intelligence (AI)-driven insights enable researchers to detect anomalies, monitor trends, and personalize interventions, resulting in more relevant and actionable health data. The technology may be used to advance the scientific understanding of how environmental, physiological, and behavioral data can be harnessed together to inform healthcare interventions and decision-making. This integration may provide an adaptable tool for advancing clinical research and accelerating the translation of scientific discovery into real-world health impact. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This award supports participation in the workshop "Theory and Applications of Elliptic Partial Differential Equations", held June 23-27, 2025 at University of California-Irvine. The workshop consists of three short courses given by experts in elliptic Partial Differential Equations (PDE). Elliptic PDE play an important role in problems from physics, biology, and geometry, and the field has seen exciting advances in recent years. The overall goals of the courses are to bring graduate students up to speed in the most active areas of elliptic PDE, to promote a sense of community within the field, and to set the course for possible future research directions. At a technical level, the courses will discuss recent advances made on free boundary problems, quasilinear and fully nonlinear geometric PDE, stochastic PDE, aggregation-diffusion equations, and steady solutions in fluid dynamics. Examples include delicate regularity results for free boundaries generated by many interacting membranes that appear, for example, in geometry and elasticity, and radial symmetry results for steady states of aggregation-diffusion equations arising in chemotaxis. The workshop gives students a chance to forge new research directions and to make connections with fellow students as well as more established mathematicians. The participants also have an opportunity to give short talks and poster presentations on their research, which serves as training in scientific communication and as a catalyst for networking. Products such as sets of lecture notes and lecture videos will be made accessible to the broader mathematical community. A website for the workshop is available at: https://ucipde2025.github.io/2025-PDE-Summer-School-Website/ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This award provides funding to support about nine (9) promising U.S.-based graduate students to participate in a two-day Doctoral Research Symposium to be held in conjunction with the ACM 2025 Conference on Computer Supported Cooperative Work & Social Computing (CSCW) in October 2025. CSCW is the premier international forum for research investigating the design and use of technologies that affect groups, organizations, communities, and networks. CSCW research spans a wide range of work, civic, and everyday life activities, as well as a wide range of computing technologies and academic disciplines. The CSCW doctoral consortia, which began in 1992, serve to bring together students and mentors across the wide range of topics, devices, institutions, and disciplines the CSCW community encompasses, providing an important place for exchange of ideas in the broader community. These events have long helped young doctoral scholars both refine their research and advance their professional development within the CSCW community under the guidance of experienced mentors in the field. Goals of the doctoral consortium include building a cohort group of new researchers who will then have a network of colleagues spread out across the world, guiding the work of new researchers by having experts in the research field mentor them and provide constructive advice, and making it possible for promising new entrants to the field to attend the conference. Students will give brief presentations about their research, followed by discussion and constructive feedback both from members of the faculty panel and other student participants. The feedback will be geared to helping students understand and articulate how their work is positioned relative to other CSCW research, whether their topics are adequately focused for thesis research projects, whether their methods are correctly chosen and applied, and whether their results are appropriately analyzed and presented. Mentors will discuss different aspects of research the research profession, including career paths, funding, work-life balance, and related topics. Together these activities will help to prepare future leaders in the field and form professional relationships that persist beyond the doctoral consortium itself. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

With support from the Environmental Chemical Sciences (ECS) program in the Division of Chemistry, Professor James Smith of the University of California, Irvine is investigating the growth mechanisms of aerosol nanoparticles involving the interactions between organic compounds with inorganic acids and bases. The composition, growth mechanisms, and properties of atmospheric nanoclusters remain unknown and have previously not been directly studied given the analytical challenges. Professor Smith and his students will perform experiments by first generating low-volatility gas phase precursors and clusters up to 2.5 nm in diameter and then measuring the physical and chemical properties of these clusters as they grow to 10 nm in diameter. Their studies could result in the identification of the major species and processes that lead to nanoparticle growth of atmospheric aerosol and could lead to improved understanding of the role of new particle formation on clouds and climate. The project will also enhance educational and professional training of undergraduate and graduate students and provide opportunities for science communication to the general public. The contribution of organics to nanoparticle growth rates will be studied for the following systems: (a) heterogeneous acid-base chemistry of semi-volatile organic acids with sulfuric acid, ammonia and amines; (b) particulate-phase accretion reaction chemistry; (c) direct partitioning of low-volatility gas-phase species. Experiments will be performed using a temperature-controlled flow tube and 560L chamber, and measurements will be made of the size-resolved composition and concentration of nanoclusters over the complete size range (1 – 10 nm). Two modeling frameworks will be employed to determine the chemical mechanisms responsible for growth. The first is a growth law analysis method that can use measured size distributions to determine whether growth is diffusion-limited or can be attributed to surface- or volume-controlled processes that indicate reactive uptake. The second approach is a chemical closure method, where a model of condensation and reactive uptake will be used to connect measured gas-phase precursor concentrations to the measured composition of nanoclusters. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This I-Corps project is based on the development of a sensor system that mimics the process of odor detection by the nose. Similar to the biological sensor system used for the sense of smell that can detect and distinguish individual odors amongst many others, this technology utilizes sensor to detect and analyze molecules in complex environments such as biological fluids or recycled water. The goal is to provide an alternative to instruments that require highly trained technicians and expensive infrastructure for operation. This approach has been used to determine the presence of a bacterial infection along with appropriate antibiotic therapy, impurities in treated water, and aerosolized chemicals. The technology may address unmet needs in medical diagnostics assessing the susceptibility of bacteria to antibiotics. The solution could rapidly determine appropriate antibiotic therapies for patients and monitor chemical byproducts in a manufacturing process and water treatment applications. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of a molecular sensor system sensor using surface chemistry and artificial neural networks. The technology is based on a nanophotonic sensing platform that uses a combination of vibrational spectroscopy and machine learning analysis to analyze complex chemical mixtures. Molecular scale control of surface chemistry has led to reproducible sensor detection at single molecule detection limits allowing for quantification of analytes down to femtomolar concentrations using surface enhanced Raman scattering (SERS). SERS spectral data is then analyzed with machine learning algorithms to “fingerprint” complex spectral response. The sensitivity, coupled with the ability to rapidly gather large SERS datasets, provides a means to measure changes in multiple chemical signals rather than only detect a single analyte in typical sensor platforms. Chemical profiles of the metabolic response of bacterial cells exposed to antibiotics provide a fingerprint to discriminate between resistance and susceptibility of bacteria after exposure to antibiotics. Using this platform, metabolic responses to antibiotics in Escherichia coli and Pseudomonas aeruginosa, two common pathogens associated with urinary tract infections, are observed below the conventional minimum inhibitory concentrations of antibiotics in 5 minutes with 99.3% accuracy, discriminating between susceptible versus resistant bacteria. This platform may have potential for providing rapid antibiotic susceptibility tests that may mitigate the rise in antimicrobial resistance in pathogenic bacteria or inform the user of toxicants in the environment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This NSF project aims to transform the way Artificial Intelligence (AI) transfers learned knowledge from simulated environments to real-world applications. The project will bring transformative change to AI by integrating symbolic reasoning with advanced hyperdimensional computing—a brain-inspired approach—thus enabling transparent and efficient interpretation of complex data under conditions where traditional deep learning struggles. This will be achieved by developing a novel neuro-symbolic framework that facilitates rapid, data-efficient knowledge transfer while maintaining interpretability across diverse cyber-physical systems. The intellectual merits of the project include its innovative use of hyperdimensional mathematics and advanced data transfer algorithms to overcome data and performance limitations, setting new benchmarks in adaptive learning. The broader impacts of the project include significant advancements in autonomous systems, robotics, and cybersecurity, as well as enhanced educational initiatives, increased opportunities for STEM, and strengthened industry collaborations. The project develops a novel neuro-symbolic framework that combines advanced hyperdimensional mathematics with deterministic finite automata (DFA) and knowledge graphs to create robust, interpretable models for knowledge transfer. By encoding high-dimensional symbolic representations, the approach enables efficient abstraction and communication of complex patterns across diverse domains. A key innovation lies in the implementation of a data-driven DFA mechanism that systematically extracts, organizes, and transfers semantic structures, ensuring reliable cross-platform data transfer and seamless adaptation between simulated and real-world environments. In addition, the framework incorporates algorithmic enhancements that facilitate dynamic data fusion and efficient pattern matching across heterogeneous datasets, further boosting its adaptability. This technical foundation is designed to reduce data requirements by more than 100 times and compress transfer learning timelines from days to minutes in simulation-to-simulation scenarios and from days to hours in simulation-to-real applications, thereby setting a new benchmark for speed, reliability, and scalability in adaptive cyber-physical systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT: Sepsis is a life-threatening medical condition characterized by high levels of inflammatory markers and multi-organ damage. Despite standard treatment, sepsis remains a leading cause of morbidity and mortality in critically ill patients, especially cancer patients. Recently, it has been shown that acupuncture can induce dopamine production, suppress inflammation, and reduce sepsis in animal studies. Several randomized controlled clinical trials have shown that acupuncture may reduce mortality in sepsis patients. However the trials were unblinded and at risk for bias. Here we propose to fill the knowledge gap by conducting a randomized controlled, patient and evaluator blinded, phase 2 trial of acupuncture (the ACTIONS trial), using sham acupuncture as control, in patients at risk for sepsis. The specific Aims are: 1) to generate preliminary data for the estimated effect size of acupuncture in reducing mortality and ICU (Intensive Care Unit) admission of sepsis patients and to determine the feasibility of conducting a randomized controlled trial of acupuncture in hospitalized patients who are at risk for sepsis; and 2) to explore whether acupuncture increases catecholamines and reduces inflammatory cytokines more than sham acupuncture. Seventy-eight patients at risk for sepsis, will be randomized to true or sham acupuncture daily for 10 days or until transfer to ICU, death, or discharge. Feasibility endpoints include as accrual rate, intervention delivery rate, attrition rate, and data completion rate. Efficacy endpoints include mortality and rate of ICU admission. Biomarker endpoints are plasma levels of catecholamines and pro-inflammatory cytokines, measured before and after the first acupuncture treatment. If this study shows that acupuncture is deemed feasible and the estimated effect size warrant a larger study, we plan to conduct a randomized controlled phase 3 study evaluate the definitive efficacy of acupuncture in improving outcomes of sepsis patients. The proposed study would be the first one acupuncture study on sepsis using sham acupuncture as control. The data will also shed light on the mechanism of action of acupuncture. This project has the potential of developing acupuncture as an innovative clinical approach in the management of sepsis. It challenges the current clinical practice paradigm and can lead to reduction of deaths due to sepsis.